Wang WenSheng, Mu ZhiYong, Zhu GuangXi, Wang Tao, Lai ShuJie, Guo Yan, Yin XinRu, Wen LiangZhi, Chen DongFeng
Department of Gastroenterology, Daping Hospital, Army Medical University, Chongqing, China.
Front Med (Lausanne). 2022 Feb 18;9:834159. doi: 10.3389/fmed.2022.834159. eCollection 2022.
There is an urgent need for non-invasive methods for predicting portal hypertensive gastropathy (PHG). This study aims to develop and validate a non-invasive method based on clinical parameters for predicting PHG in patients with liver cirrhosis (LC).
The overall survival (OS) and hepatocellular carcinoma (HCC)-free survival were evaluated in LC patients, both with and without PHG. A prediction model for PHG was then constructed based on a training dataset that contained data on 492 LC patients. The discrimination, calibration, and clinical utility of the predicting nomogram were assessed using the C-index, calibration plot, and decision curve analysis. Internal validation was conducted using a bootstrapping method, and further external validation using data on the 208 other patients.
LC patients with PHG had a worse prognosis compared with those without PHG. A nomogram was constructed using clinical parameters, such as age, hemoglobin content, platelet count and Child-Pugh class. The C-index was 0.773 (95% CI: 0.730-0.816) in the training cohort, 0.761 after bootstrapping and 0.745 (95% CI: 0.673-0.817) in the validation cohort. The AUC values were 0.767, 0.724, and 0.756 in the training, validation and total cohorts, respectively. Well-fitted calibration curves were observed in the training and validation cohorts. Decision curve analysis demonstrated that the nomogram was clinically useful at a threshold of 15%.
The nomogram constructed to predict the risk of developing PHG was found to be clinically viable. Furthermore, PHG is an independent risk factor for OS of LC, but not for the occurrence of HCC.
迫切需要用于预测门静脉高压性胃病（PHG）的非侵入性方法。本研究旨在开发并验证一种基于临床参数的非侵入性方法，用于预测肝硬化（LC）患者的PHG。
评估了有和没有PHG的LC患者的总生存期（OS）和无肝细胞癌（HCC）生存期。然后基于包含492例LC患者数据的训练数据集构建了PHG预测模型。使用C指数、校准图和决策曲线分析评估预测列线图的辨别力、校准度和临床实用性。采用自举法进行内部验证，并使用另外208例患者的数据进行进一步的外部验证。
与没有PHG的LC患者相比，有PHG的患者预后更差。使用年龄、血红蛋白含量、血小板计数和Child-Pugh分级等临床参数构建了列线图。训练队列中的C指数为0.773（95%CI：0.730-0.816），自举后为0.761，验证队列中为0.745（95%CI：0.673-百分之0.817）。训练、验证和总队列中的AUC值分别为0.767、0.724和0.756。在训练和验证队列中观察到拟合良好的校准曲线。决策曲线分析表明，列线图在阈值为15%时具有临床实用性。
发现构建的用于预测发生PHG风险的列线图在临床上是可行的。此外，PHG是LC患者OS的独立危险因素，但不是HCC发生的独立危险因素。
